Role Summary
We are seeking a
GenAI Engineer / Architect to design and deliver
enterprise-grade AI solutions including
RAG pipelines, AI agents, orchestration frameworks, and governance models.
The role involves building scalable, production-ready GenAI systems using modern LLM platforms like Microsoft Azure OpenAI and integrating them into enterprise ecosystems.
Key ResponsibilitiesGenAI Solution Architecture
- Design end-to-end GenAI solutions using LLMs, RAG, embeddings, and vector search.
- Define scalable architectures for enterprise AI applications.
RAG & Search Systems
- Build RAG pipelines (chunking, embeddings, retrieval, ranking).
- Work with vector databases such as Azure AI Search, Redis, PostgreSQL.
- Implement citation validation and hallucination detection mechanisms.
Agentic AI & Orchestration
- Design and develop AI agents and multi-agent systems.
- Implement orchestration workflows using tools like Workato, AWS services, DigitalNet.
- Build AI-driven automation pipelines.
Document Intelligence
- Develop document ingestion pipelines (OCR, metadata extraction, enrichment).
- Handle structured and unstructured data processing.
Cloud & Deployment
- Deploy AI workloads on Azure (OpenAI, AI Search, ML, AKS).
- Work across multi-cloud environments (Azure, AWS).
- Implement CI/CD pipelines and DevSecOps practices.
Responsible AI & Governance
- Implement Responsible AI frameworks (fairness, bias, explainability).
- Align with standards like NIST AI RMF and enterprise governance tools (CredoAI).
- Lead POCs, solution evaluations, and technical documentation.
Required Skills GenAI & LLMs- Strong experience in:
- RAG architectures
- Prompt engineering & evaluation
- LLM platforms (Azure OpenAI, Claude, Gemini)
- Hallucination detection & response validation
AI Engineering
- Experience building AI agents and orchestration frameworks.
- Knowledge of LangChain / agent frameworks (preferred).
Data & Search- Experience with vector databases:
- Azure AI Search
- Redis
- PostgreSQL
Document Processing
- Experience with OCR, metadata extraction, document pipelines.
Cloud & DevOps- Strong experience with:
- Azure & AWS
- Kubernetes (AKS)
- CI/CD & DevSecOps
Governance- Experience with:
- Responsible AI frameworks
- AI governance tools (e.g., CredoAI)
- Compliance frameworks (e.g., NIST AI RMF)
Required Certifications
- Azure AI Fundamentals (AI-900)
- Azure Data Fundamentals (DP-900)
- Responsible AI certifications
- AWS Machine Learning Specialty
- TensorFlow Developer Certification
- Kubernetes (CKA/CKAD)
- SAFe Agile Certification (ASE preferred)
Preferred Certifications
- Azure AI Engineer (AI-102)
- Azure Data Scientist (DP-100)
- Azure Solutions Architect (AZ-305)
- Azure Developer (AZ-204)
Skills: aws,azure openai,langchain,azure,nist framework,llm,gen ai,ocr,azure certification,credoai,azure data scientist,azure solutions architect,azure ai engineer
